
import os
from IPython.display import display, HTML
display(HTML("<style>.container { width:100% !important; }</style>"))


# If you want to run this notebook locally, copy the output of the next cell into the next line of this cell.
# antenna = "54"
# csv_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/_rtp_summary_'
# auto_metrics_folder = '/lustre/aoc/projects/hera/H5C/H5C_Notebooks/auto_metrics_inspect'
# os.environ["ANTENNA"] = antenna
# os.environ["CSV_FOLDER"] = csv_folder
# os.environ["AUTO_METRICS_FOLDER"] = auto_metrics_folder


# Use environment variables to figure out path to the csvs and auto_metrics
antenna = os.environ["ANTENNA"]
csv_folder = os.environ["CSV_FOLDER"]
auto_metrics_folder = os.environ["AUTO_METRICS_FOLDER"]
print(f'antenna = "{antenna}"')
print(f'csv_folder = "{csv_folder}"')
print(f'auto_metrics_folder = "{auto_metrics_folder}"')

antenna = "65"
csv_folder = "/home/obs/src/H5C_Notebooks/_rtp_summary_"
auto_metrics_folder = "/home/obs/src/H5C_Notebooks/auto_metrics_inspect"


display(HTML(f'<h1 style=font-size:50px><u>Antenna {antenna} Report</u><p></p></h1>'))


import numpy as np
import pandas as pd
pd.set_option('display.max_rows', 1000)
import glob
import re
from hera_notebook_templates.utils import status_colors, Antenna


# load csvs and auto_metrics htmls in reverse chronological order
csvs = sorted(glob.glob(os.path.join(csv_folder, '*.csv')))[::-1]
print(f'Found {len(csvs)} csvs in {csv_folder}')
auto_metric_htmls = sorted(glob.glob(auto_metrics_folder + '/auto_metrics_inspect_*.html'))[::-1]
print(f'Found {len(auto_metric_htmls)} auto_metrics notebooks in {auto_metrics_folder}')

Found 75 csvs in /home/obs/src/H5C_Notebooks/_rtp_summary_
Found 71 auto_metrics notebooks in /home/obs/src/H5C_Notebooks/auto_metrics_inspect


# Per-season options
mean_round_modz_cut = 4
dead_cut = 0.4
crossed_cut = 0.0

def jd_to_summary_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/_rtp_summary_/rtp_summary_{jd}.html'

def jd_to_auto_metrics_url(jd):
    return f'https://htmlpreview.github.io/?https://github.com/HERA-Team/H5C_Notebooks/blob/main/auto_metrics_inspect/auto_metrics_inspect_{jd}.html'


this_antenna = None
jds = []

# parse information about antennas and nodes
for csv in csvs:
    df = pd.read_csv(csv)
    for n in range(len(df)):
        # Add this day to the antenna
        row = df.loc[n]
        antnum = row['Ant']
        if antnum != int(antenna):
            continue
            
        if this_antenna is None:
            this_antenna = Antenna(row['Ant'], row['Node'])
        jd = [int(s) for s in re.split('_|\.', csv) if s.isdigit()][-1]
        jds.append(jd)
        this_antenna.add_day(jd, row)
        break


# build dataframe
to_show = {'JDs': [f'<a href="{jd_to_summary_url(jd)}" target="_blank">{jd}</a>' for jd in jds]}
to_show['A Priori Status'] = [this_antenna.statuses[jd] for jd in jds]

df = pd.DataFrame(to_show)

# create bar chart columns for flagging percentages:
bar_cols = {}
bar_cols['Auto Metrics Flags'] = [this_antenna.auto_flags[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jee)'] = [this_antenna.dead_flags_Jee[jd] for jd in jds]
bar_cols[f'Dead Fraction in Ant Metrics (Jnn)'] = [this_antenna.dead_flags_Jnn[jd] for jd in jds]
bar_cols['Crossed Fraction in Ant Metrics'] = [this_antenna.crossed_flags[jd] for jd in jds]
bar_cols['Flag Fraction Before Redcal'] = [this_antenna.flags_before_redcal[jd] for jd in jds]
bar_cols['Flagged By Redcal chi^2 Fraction'] = [this_antenna.redcal_flags[jd] for jd in jds]
for col in bar_cols:
    df[col] = bar_cols[col]

z_score_cols = {}
z_score_cols['ee Shape Modified Z-Score'] = [this_antenna.ee_shape_zs[jd] for jd in jds]
z_score_cols['nn Shape Modified Z-Score'] = [this_antenna.nn_shape_zs[jd] for jd in jds]
z_score_cols['ee Power Modified Z-Score'] = [this_antenna.ee_power_zs[jd] for jd in jds]
z_score_cols['nn Power Modified Z-Score'] = [this_antenna.nn_power_zs[jd] for jd in jds]
z_score_cols['ee Temporal Variability Modified Z-Score'] = [this_antenna.ee_temp_var_zs[jd] for jd in jds]
z_score_cols['nn Temporal Variability Modified Z-Score'] = [this_antenna.nn_temp_var_zs[jd] for jd in jds]
z_score_cols['ee Temporal Discontinuties Modified Z-Score'] = [this_antenna.ee_temp_discon_zs[jd] for jd in jds]
z_score_cols['nn Temporal Discontinuties Modified Z-Score'] = [this_antenna.nn_temp_discon_zs[jd] for jd in jds]
for col in z_score_cols:
    df[col] = z_score_cols[col]

ant_metrics_cols = {}
ant_metrics_cols['Average Dead Ant Metric (Jee)'] = [this_antenna.Jee_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Dead Ant Metric (Jnn)'] = [this_antenna.Jnn_dead_metrics[jd] for jd in jds]
ant_metrics_cols['Average Crossed Ant Metric'] = [this_antenna.crossed_metrics[jd] for jd in jds]
for col in ant_metrics_cols:
    df[col] = ant_metrics_cols[col]

redcal_cols = {}
redcal_cols['Median chi^2 Per Antenna (Jee)'] = [this_antenna.Jee_chisqs[jd] for jd in jds]
redcal_cols['Median chi^2 Per Antenna (Jnn)'] = [this_antenna.Jnn_chisqs[jd] for jd in jds]   
for col in redcal_cols:
    df[col] = redcal_cols[col]

# style dataframe
table = df.style.hide_index()\
          .applymap(lambda val: f'background-color: {status_colors[val]}' if val in status_colors else '', subset=['A Priori Status']) \
          .background_gradient(cmap='viridis', vmax=mean_round_modz_cut * 3, vmin=0, axis=None, subset=list(z_score_cols.keys())) \
          .background_gradient(cmap='bwr_r', vmin=dead_cut-.25, vmax=dead_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .background_gradient(cmap='bwr_r', vmin=crossed_cut-.25, vmax=crossed_cut+.25, axis=0, subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .background_gradient(cmap='plasma', vmax=4, vmin=1, axis=None, subset=list(redcal_cols.keys())) \
          .applymap(lambda val: 'font-weight: bold' if val < dead_cut else '', subset=list([col for col in ant_metrics_cols if 'dead' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val < crossed_cut else '', subset=list([col for col in ant_metrics_cols if 'crossed' in col.lower()])) \
          .applymap(lambda val: 'font-weight: bold' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .applymap(lambda val: 'color: red' if val > mean_round_modz_cut else '', subset=list(z_score_cols.keys())) \
          .bar(subset=list(bar_cols.keys()), vmin=0, vmax=1) \
          .format({col: '{:,.4f}'.format for col in z_score_cols}) \
          .format({col: '{:,.4f}'.format for col in ant_metrics_cols}) \
          .format('{:,.2%}', na_rep='-', subset=list(bar_cols.keys())) \
          .set_table_styles([dict(selector="th",props=[('max-width', f'70pt')])])


display(HTML(f'<h2>Antenna {antenna}, Node {this_antenna.node}:</h2>'))
HTML(table.render(render_links=True, escape=False))


html_to_display = ''
for am_html in auto_metric_htmls:
    # read html into a list of lines
    with open(am_html) as f:
        lines = f.readlines()
    
    # find section with this antenna's metric plots and add to html_to_display
    jd = [int(s) for s in re.split('_|\.', am_html) if s.isdigit()][-1]
    try:
        section_start_line = lines.index(f'<h2>Antenna {antenna}: {jd}</h2>\n')
    except ValueError:
        continue
    html_to_display += lines[section_start_line].replace(str(jd), f'<a href="{jd_to_auto_metrics_url(jd)}" target="_blank">{jd}</a>')
    for line in lines[section_start_line + 1:]:
        html_to_display += line
        if '<hr' in line: 
            break


HTML(html_to_display)

JDs	A Priori Status	Auto Metrics Flags	Dead Fraction in Ant Metrics (Jee)	Dead Fraction in Ant Metrics (Jnn)	Crossed Fraction in Ant Metrics	Flag Fraction Before Redcal	Flagged By Redcal chi^2 Fraction	ee Shape Modified Z-Score	nn Shape Modified Z-Score	ee Power Modified Z-Score	nn Power Modified Z-Score	ee Temporal Variability Modified Z-Score	nn Temporal Variability Modified Z-Score	ee Temporal Discontinuties Modified Z-Score	nn Temporal Discontinuties Modified Z-Score	Average Dead Ant Metric (Jee)	Average Dead Ant Metric (Jnn)	Average Crossed Ant Metric	Median chi^2 Per Antenna (Jee)	Median chi^2 Per Antenna (Jnn)
2459594	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.913476	14.874347	78.556297	78.925751	22.290713	28.739413	31.236811	33.689065	0.0326	0.0326	0.0005	1.253738	1.251880
2459593	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.867513	16.051614	82.625314	84.419260	31.484899	38.244051	13.958369	11.917618	0.0344	0.0344	0.0016	1.211856	1.209610
2459592	RF_maintenance	100.00%	100.00%	100.00%	0.00%	-	-	1.649073	1.783860	7.421566	6.483841	1.303470	3.003936	-1.410390	0.657086	0.0261	0.0276	0.0009	nan	nan
2459591	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	18.761975	20.360555	96.531045	97.925249	26.516207	31.926757	1.727257	2.682054	0.0343	0.0344	0.0011	1.185943	1.185515
2459590	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	21.537237	23.791696	89.734133	91.290634	28.658222	34.273460	3.896351	4.794310	0.0337	0.0338	0.0019	1.266864	1.268558
2459589	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.691557	21.631089	83.426801	84.644823	16.976860	22.008332	19.201416	17.564137	0.0330	0.0336	0.0015	1.207623	1.206649
2459588	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.492264	14.234752	101.232545	102.887492	22.024496	25.054423	14.605301	13.385771	0.0314	0.0340	0.0010	1.176235	1.173556
2459587	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	19.015273	21.118982	135.313847	137.981368	6.603468	8.083662	12.156312	12.969766	nan	nan	nan	0.974400	1.314400
2459586	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.725789	17.460912	31.759525	31.912081	10.094400	11.698446	5.958679	7.358168	0.0334	0.0351	0.0014	1.232511	1.231795
2459585	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	26.077447	26.194055	10.321289	10.408151	9.358239	10.227726	2.529440	4.249580	0.0282	0.0303	0.0008	0.000000	0.000000
2459584	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	23.947059	27.098164	111.696186	113.088220	32.423518	41.901795	23.787710	30.729868	0.0311	0.0339	0.0016	0.000000	0.000000
2459583	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.582940	18.224993	34.549138	34.984427	20.134247	23.692107	0.261205	0.561342	0.0335	0.0382	0.0018	1.208904	1.201534
2459582	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.647133	16.452498	31.080665	31.760268	24.015330	28.035210	0.270593	0.640909	0.0303	0.0329	0.0014	1.277400	1.276091
2459581	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.315447	22.324381	36.038279	35.876074	19.060469	22.939551	0.525888	0.806498	0.0316	0.0354	0.0020	1.208168	1.206719
2459580	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.428302	16.470309	36.185647	36.753109	21.247068	24.406300	0.053210	0.537423	0.0310	0.0350	0.0017	0.000000	0.000000
2459579	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459578	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	2.219834	1.827846	3.000390	2.216921	1.124545	0.811106	1.809463	3.042354	0.0278	0.0279	0.0015	nan	nan
2459577	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	19.976578	21.250169	33.471717	33.565250	21.185812	25.108060	0.365582	0.803534	0.0302	0.0328	0.0016	1.240123	1.241051
2459576	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459575	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459574	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.671501	14.959157	25.299672	25.398190	20.728674	24.015981	1.312518	1.709221	0.0316	0.0348	0.0014	1.241870	1.243910
2459573	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.256553	15.920887	43.534378	43.983365	24.962778	28.509788	1.103282	2.008155	0.0327	0.0357	0.0018	0.000000	0.000000
2459572	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.125151	16.054563	25.424623	25.748884	16.090007	18.050134	2.494328	3.405478	0.0331	0.0348	0.0029	1.253482	1.253529
2459571	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	1.677928	1.480647	2.918110	2.297090	1.701375	2.470980	1.671261	3.003284	0.0278	0.0291	0.0015	nan	nan
2459570	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	19.571344	20.398981	27.155272	27.225290	1.334326	1.784280	3.685069	5.377854	0.0453	0.0433	0.0032	1.206283	1.211400
2459569	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	19.458882	18.904327	33.412922	33.434523	10.524742	10.771766	8.422297	9.212042	0.0332	0.0361	0.0024	1.232680	1.232221
2459566	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.081581	14.239733	33.177698	32.443150	19.136876	20.138719	-0.206488	4.759424	0.0309	0.0310	0.0014	1.336423	1.358147
2459565	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	-0.160317	-0.160317	-0.179841	-0.179841	0.501946	0.501946	0.023484	0.023484	nan	nan	nan	0.000000	0.000000
2459564	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	13.366210	13.849711	35.212853	35.518970	2.472371	2.463746	0.565749	1.181251	0.0324	0.0332	0.0012	1.261615	1.265763
2459563	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	15.475376	16.007834	67.264343	67.730791	19.906804	22.600329	1.625746	2.379296	0.0350	0.0355	0.0016	1.406696	1.413123
2459562	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.590279	9.910559	17.288244	17.458751	2.577803	2.823213	0.668847	0.985231	0.0324	0.0364	0.0017	1.241234	1.241251
2459561	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.306676	10.509533	16.467138	16.567362	2.867156	2.982271	1.042931	1.725777	0.0315	0.0355	0.0017	1.269545	1.274884
2459560	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.438772	9.606025	16.914023	16.854576	2.658390	3.131884	0.650260	0.786901	0.0319	0.0366	0.0018	1.183285	1.184989
2459559	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	nan	nan	inf	inf	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459558	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.511359	16.426352	34.652976	35.339621	21.849205	23.576981	1.271852	1.764674	0.0332	0.0364	0.0023	1.217597	1.220118
2459557	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0280	0.0294	0.0017	nan	nan
2459556	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	16.900667	16.852489	37.458128	38.306989	19.680419	21.223461	2.870348	4.349903	0.0317	0.0342	0.0019	1.356516	1.370833
2459554	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0320	0.0345	0.0023	nan	nan
2459553	RF_maintenance	-	100.00%	100.00%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0303	0.0323	0.0014	nan	nan
2459552	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	19.544633	20.067304	50.546918	50.539036	29.251338	32.311163	3.212530	3.494726	0.0322	0.0341	0.0029	0.000000	0.000000
2459551	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.498526	9.542361	20.462442	20.515814	3.535435	4.323555	1.083079	1.517165	0.0318	0.0353	0.0018	1.257726	1.260883
2459550	RF_maintenance	-	98.35%	98.35%	0.00%	-	-	nan	nan	nan	nan	nan	nan	nan	nan	0.0449	0.0467	0.0008	nan	nan
2459549	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	14.535781	14.851630	37.995974	38.156601	21.253957	23.160651	1.154166	1.687931	0.0321	0.0351	0.0022	1.377022	1.382243
2459542	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.700095	21.275399	77.161259	77.391162	1.089446	1.876514	1.256446	1.917145	0.0336	0.0339	0.0015	1.255342	1.259273
2459541	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.084491	9.790563	36.009349	36.740132	255.556587	245.830898	20.665481	15.313627	0.0332	0.0374	0.0019	1.284924	1.288375
2459540	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	13.706079	14.711727	17.192162	17.581239	4.182825	5.228020	0.705592	1.059189	0.0319	0.0357	0.0006	1.260280	1.264133
2459536	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	25.779022	27.909630	65.732656	65.615957	29.621302	31.759087	2.429465	2.979339	0.0317	0.0334	0.0024	0.000000	0.000000
2459535	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	10.690146	11.869940	15.973196	16.132283	2.133305	5.442742	0.161213	0.637955	0.0341	0.0360	0.0010	1.316580	1.347481
2459534	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	11.368120	12.456376	14.842803	14.911137	2.298282	3.962507	0.100709	0.190840	0.0318	0.0322	0.0010	1.250183	1.251939
2459533	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	17.527057	18.237888	35.408019	35.785638	18.169347	20.847174	1.301167	2.114318	0.0308	0.0342	0.0007	1.343997	1.346357
2459532	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	20.425306	21.171669	47.718968	48.534649	22.458857	25.652095	0.789880	1.284513	0.0315	0.0346	0.0007	0.000000	0.000000
2459530	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	9.778861	10.327972	15.095644	15.173637	3.559025	4.335619	0.534392	0.772301	0.0317	0.0348	0.0010	1.330404	1.338034
2459527	RF_maintenance	0.00%	-	-	-	100.00%	0.00%	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	nan	0.000000	0.000000
2459524	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	24.873703	25.861918	53.587796	54.060971	40.354741	34.854289	0.108403	1.014126	0.0318	0.0332	0.0011	0.000000	0.000000
2459523	RF_maintenance	100.00%	-	-	-	100.00%	0.00%	22.809644	21.157674	52.281298	51.766319	39.345146	48.350614	14.630835	14.066316	nan	nan	nan	1.743728	1.790759
2459522	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	17.940610	22.633500	51.377342	52.509431	10.712357	23.582680	1.389515	2.370685	0.0329	0.0312	0.0015	0.000000	0.000000
2459513	RF_maintenance	0.00%	100.00%	100.00%	0.00%	-	-	2.009624	1.812831	2.976478	2.546318	0.374838	0.463081	1.075142	2.071096	0.0315	0.0334	0.0013	nan	nan
2459508	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	26.405591	30.234316	50.064620	51.031393	18.047530	15.586668	12.882508	14.895477	0.0297	0.0311	0.0013	0.000000	0.000000
2459505	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	23.304565	30.229816	47.017057	49.365882	7.117124	10.134851	0.765281	2.451647	0.0311	0.0352	0.0045	1.246038	1.305325
2459503	RF_maintenance	100.00%	100.00%	100.00%	0.00%	100.00%	0.00%	26.926742	30.616574	82.828494	83.517672	33.788889	33.380656	2.345049	3.508538	0.0278	0.0318	0.0039	0.000000	0.000000

Antenna Season Report Notebook¶

Antenna 65 Report

Load relevant info from summary CSVs¶

Table 1: Per-Night RTP Summary Info For This Atenna¶

Antenna 65, Node 3:

Load antenna metric spectra and waterfalls from auto_metrics notebooks.¶

Figure 1: Antenna autocorrelation metric spectra and waterfalls.¶

Antenna 65: 2459595

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Load antenna metric spectra and waterfalls from `auto_metrics` notebooks.¶